Randomized Hough Transform: Improved ellipse detection with comparison

R.A. Mclaughlin

doi:10.1016/S0167-8655(98)00010-5

Randomized Hough Transform: Improved ellipse detection with comparison

R.A. Mclaughlin

Graduate Research School

Research output: Contribution to journal › Article › peer-review

216 Citations (Scopus)

Abstract

We describe an algorithm for the detection of ellipse shapes in images, using the Randomized Hough Transform. The method is compared with three other Hough-based algorithms. Tests are performed using both noise-free and noisy images, and several real-world images. The algorithm was found to give improvements in accuracy, and a reduction in computation time and the number of false alarms detected. A program allowing the reader to experiment with these algorithms can be found at the WWW address http://ciips.ee.uwa.edu.au/Papers/Journal_Papers/1998/01/Index.html. (C) 1998 Elsevier Science B.V. All rights reserved.

Original language	English
Pages (from-to)	299-305
Journal	Pattern Recognition Letters
Volume	19
Issue number	3-4
DOIs	https://doi.org/10.1016/S0167-8655(98)00010-5
Publication status	Published - 1998

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abstract = "We describe an algorithm for the detection of ellipse shapes in images, using the Randomized Hough Transform. The method is compared with three other Hough-based algorithms. Tests are performed using both noise-free and noisy images, and several real-world images. The algorithm was found to give improvements in accuracy, and a reduction in computation time and the number of false alarms detected. A program allowing the reader to experiment with these algorithms can be found at the WWW address http://ciips.ee.uwa.edu.au/Papers/Journal_Papers/1998/01/Index.html. (C) 1998 Elsevier Science B.V. All rights reserved.",

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AB - We describe an algorithm for the detection of ellipse shapes in images, using the Randomized Hough Transform. The method is compared with three other Hough-based algorithms. Tests are performed using both noise-free and noisy images, and several real-world images. The algorithm was found to give improvements in accuracy, and a reduction in computation time and the number of false alarms detected. A program allowing the reader to experiment with these algorithms can be found at the WWW address http://ciips.ee.uwa.edu.au/Papers/Journal_Papers/1998/01/Index.html. (C) 1998 Elsevier Science B.V. All rights reserved.

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DO - 10.1016/S0167-8655(98)00010-5

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JF - Pattern Recogniton Letters

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Randomized Hough Transform: Improved ellipse detection with comparison

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